We had previously developed methods for quantitative traits using individuals and their parents and exploiting the apparent tendency for trait-related SNPs to be overtransmitted to offspring with a relatively extreme value of the trait. The method assesses transmissions in relation to trait values using polytomous logistic regression. We noticed that the same mathematical approach can be applied to case-parents data to assess gene-by-environment interaction, because if the joint effects of a SNP and an exposure are super-multiplicative then affected individuals with a high level of the exposure will demonstrate an increased tendency to have inherited the SNP, compared to affected individuals with low exposure. This year we published this approach to using case-parent triads to assess multiplicative gene-by-environment interaction. We had previously developed methods for qualitative traits using multiple-SNP genotypes for affected individuals and their parents in a method called TRIMM (triad multi-marker). The testing approach is robust against bias due to population stratification. In work published this year we use likelihood methods to estimate both offspring and maternal relative risks associated with one and two copies of a particular candidate haplotype. The method yields unbiased estimation for adequate sample sizes, and when multiple tightly-linked SNPs are studied can allow the analyst to distinguish between a protective effect of one candidate haplotype and a deleterious effect of that haplotypes complement. Such Yin-Yang haplotype pairs have recently been reported to be surprisingly common in the human genome, so it is important to be able to resolve that inferential conundrum. We have now further extended the approach to allow testing for haplotype-by-environment interaction, via a method we call GEI-TRIMM. The paper describing this approach and characterizing its performance through simulations is currently undergoing review. In another project, we are estimating the asymmetry that would exist in family history data secondary to the existence of a maternally-mediated genetic effect. We applied this strategy to family history data from the Sister Study, and found evidence that maternal grandmothers of young-onset (under 50) cases of breast cancer were more likely to have had breast cancer than were their paternal grandmothers. This suggests there may be maternally-mediated genetic risk factors for breast cancer, or that mitochondrial variants play a role. A particularly important design we are now considering involves a "tetrad" structure, with one affected and one unaffected offspring, in addition to the two parents. The discordant sib pair allows estimation of effects of exposures, while the embedded case-parent triad allows detection of haplotypes that confer either protection or risk. The tetrad analyzed together should provide a powerful design for assessing gene-by-environment interaction. We will be working on developing and evaluating methods for use with the tetrad design, in order to apply it to the Two Sister Study. This study is currently enrolling nuclear families where one daughter developed breast cancer before age 50 and the other daughter is unaffected. Inherited genotypes, together with tumor characteristics, will need to be explored to investigate factors that predict the clinical course following treatment, and improved methods will also need to be developed in that context. Another project considered the problem of designing an association study for identifying genetic variants that confer susceptibility to preterm birth. While risk is clearly related to environmental factors, genetic factors are also involved. The evidence coming to light in epidemiology based on large population family linkage efforts, points to a pattern where the paternal genome has little or nothing to do with risk, leaving as plausible maternally expressed genes, either in the mother herself or expressed in the fetus, due to silencing or near-silencing of the paternal copy. We compared three approaches to design and concluded that the commonly applied case-mother/control-mother approach is not optimal for studying preterm birth, and that case-parent triad approaches should be considered. Such a design is currently being used in a study that is ongoing in Buenos Aires, Argentina, where some 1200 very low birth weight babies and their two parents are being enrolled (Kleeberger PI). All of these babies are preterm and we should be able to use this sample to identify genetic variants related to preterm birth. We will also need to refine our methods to take into account the degree of prematurity in these babies, as a partially quantitative trait, and account for the extensive environmental and medical history data being collected by the neonatal intensive care units.